In the cloud computing era, with increasing computing requirements of the society, a scale of a data center also rapidly expands. However, for a huge data center, average utilization of data center resources is relatively low, and most devices are idle. This causes a heavy energy consumption burden to the data center. How to reduce energy consumption of a data center is a current severe challenge to a data center. Currently, in a data center, a virtualization technology is used, such that energy consumption of the data center can be effectively reduced, and data center resource utilization can be increased. A virtual data center is a service type of a flexible self-service that is formed on the basis of a cloud computing service and that provides rapid deployment, a real-time response, immediate lease, allocation on demand, and dynamic resource extension. Under this new trend, a resource request of each tenant may be abstracted into a virtual data center (Virtual Data Center, VDC for short) constituted by a group of virtual machines (Virtual Machine, VM for short), and each VM is corresponding to specified resources (including a CPU, a memory, a hard disk, and the like). In addition, for transfer of data and an object file, a communications link with guaranteed bandwidth also needs to be established between VMs, so as to satisfy a requirement of communication between the VMs. Because VM arrangement is tightly coupled with a route for VM communication bandwidth, a process of mapping a VDC to a bottom-layer physical network becomes very complex. A VDC mapping problem refers to a problem about how to fully utilize physical network resources when a VDC is mapped to a physical network.
In the VDC mapping process, main factors to be considered include reliability, bandwidth consumption, and energy consumption of physical facilities. Current VDC mapping may be classified into the following two cases: In a first case, all VMs in a VDC are evenly allocated to each physical server, so as to achieve minimum impact between the VMs, and implement load balancing between bottom-layer physical facilities; in a second case, VMs in a VDC are deployed as many as possible in one physical server, so as to minimize link consumption between the VMs. During VDC mapping, from a perspective of energy consumption and bandwidth consumption, all VMs in a VDC need to be integrated to the most extent, to occupy as few physical servers as possible. In this way, bandwidth consumption between servers is reduced, and another unused physical server may be disabled, thereby achieving an objective of energy saving. However, VM integration may cause low reliability of a VDC, and a failure of one physical server may cause a large-scale VDC failure. From a perspective of reliability, VMs in a VDC need to be scattered. Obviously, energy saving and reliability are two contradictory indicators. An existing mapping algorithm cannot well resolve the VDC mapping problem.